How do you know if your prompt is good?
Your AI agent completed the task. But how do you know if it actually did a good job?
Jeff Keyes (AI Product Strategist & CTO at Allstacks) explains why building reliable AI agents requires more than writing effective prompts.
As artificial intelligence transforms software development, companies are increasingly building AI-powered products where customers interact directly with intelligent agents rather than traditional software interfaces.
But this creates a new challenge.
How do you measure whether an AI agent is producing accurate, useful, and reliable results?
Jeff argues that product teams need AI evaluations, also known as AI evals, to measure how well their agents perform.
Instead of simply trusting an AI agent's output, companies need systems that assess its responses, score its performance, and identify areas for improvement.
That could even involve using another AI agent to evaluate the first one.
And according to Jeff, product managers need to take ownership of this process.
As AI agents become part of everyday products, product management is evolving beyond traditional feature development toward evaluating AI behavior, measuring performance, and continuously improving the customer experience.
The future of AI products isn't just about building smarter agents. It's about knowing whether those agents are actually working.
Would you trust an AI agent to evaluate another AI agent?
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